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Understanding and addressing seabird bycatch in Alaska demersal longline fisheries
Authors:Kimberly S Dietrich  Julia K Parrish  Edward F Melvin  
Institution:aSchool of Aquatic and Fishery Sciences/Washington Sea Grant, University of Washington, 3716 Brooklyn Avenue NE, Seattle, WA 98105-6716, USA;bSchool of Aquatic and Fishery Sciences, University of Washington, Box 355020, Seattle, WA 98195-5020, USA
Abstract:The incidental catch of seabirds in longline fisheries is a global conservation concern. In Alaska, annual seabird bycatch in demersal longline fisheries ranged between 10,300 and 26,300 birds (1995–2001). We explore the relationship between four categories of potential forcing factors (temporal, spatial, environmental, and fisheries-related) and seabird bycatch rates in Alaska demersal longline fisheries to provide practical management alternatives that could significantly reduce seabird bycatch.Separate generalized linear or additive models (GLM or GAM, respectively) were created for several combinations of seabird group, fishery and large geographic region. Across nearly all models, “vessel” was the most influential factor explaining seabird bycatch rate variation. Rather than a single variable, vessel is an amalgam of unmeasured forcing factors many of which could not be separated out in this data set (e.g., longline sink rate, vessel setting speed, line deployment location relative to propeller direction). A separate vessel-specific analysis also supported the multivariate results that performance of an individual vessel is overwhelmingly important (i.e., some vessels have consistently high or low bycatch rates from year to year). Therefore, vessel-specific performance is a critical management option.The effects of temporal (annual, month, and breeding phenology) and spatial variables were also moderately influential on seabird bycatch rates. Our results suggest that seasonal adjustments in the Alaska longline fishery have potential for overall bycatch reductions, but vague seabird management objectives could have huge unintended and undesirable consequences when implementing temporal adjustments. Other variables (environmental and other fishing-related factors) were frequently significant but contributed a small amount to overall explained deviance.Based on this study, we conclude that a vessel-specific management approach would be the most effective and efficient means to reduce seabird bycatch in Alaska.
Keywords:Incidental catch  Seabird-fishery interaction  Generalized linear model  Generalized additive model
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